What you'll learn:
Insights of Azure Data Services - Storage Services, ADF V2, Azure Databricks and SQL DW (Synapse Analytics)
Creating and Managing data related Azure services
Practical experience with downloadable datasets
Design concepts for big data processing on Azure Data Lake
Securing Data on Blob Storage using SAS URLs + Lifecycle Policies to archive data with auto tier change
End to End Data load pipeline (Source -> Raw Layer -> Curated -> Consumption)

Requirements
ETL or Database Knowledge is expected
Basic Azure Knowledge is plus
Spark knowledge will speed up learning Azure Databricks

Description
Learn All in One Azure Data Engineering services along with hands-on (requirement gathering to implementation)

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Recently added sessions:

Added code snippets for Databricks <-> SQL Server using JDBC

Data Generator code added. Now you can generate your own datasets for this workshop.

Copy data from Azure SQL to Azure SQL without ADF (kind of linked server)

ADF Code promotion - manual activity

Dynamically change DB connection in ADF (Parameterizing linked service)

Visible comparison of Blob and Azure Data Lake Gen2 storage using data analytics through Azure Databricks.

NY Taxi data files source link added in resources section

Integrate Key Vault with Azure Databricks and extract secrets via Secret Scope

Use Blob SDK in Azure Databricks to read/write files on blob like IO operations

Connecting to SQL Server with pyodbc in Azure Databricks

Datasets used in this course are now available to download. Visit Azure Data Factory section.

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We will execute a small project. It will help you to learn:

1) Design concepts - How to design big data system. Terminologies of each components/layers.

2) Hands-on - We will be creating required Azure data services and will look various options available.

3) Tips and Tricks

4) Helps in DP-200 and DP-201 certification preparation.

Technologies you will learn:

Azure Data Factory V2, Databricks (using Standard cluster), Storage Services, SQL Synapse Analytics (DB part)

Course highlights:

1) Resources: Links to external resource for further reading

2) Datasets : Download and use dataset used in this course. Do more practice.

3) Architecture and Design : Start learning on how to deign the data load on cloud platform.

Who this course is for
Beginners to Azure Data World
ETL Developers
Database Professionals

Citación :

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